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Analytics ⇄ Data warehouse

Adobeanalytics to Apache Pinot integration — real-time data sync

Keep Adobeanalytics and Apache Pinot in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

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Adopted by fast-scaling companies moving mission-critical data in real time

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Why teams connect Adobeanalytics and Apache Pinot

Flow Adobeanalytics data into Apache Pinot in real time — no exports, no schedulers, no custom scripts.

Adobeanalytics is a read-only source: Stacksync reads its data in real time and delivers it into Apache Pinot, so Apache Pinot always reflects the current state of Adobeanalytics — without exports, scripts, or schedulers.

Adobeanalytics is where teams explore, visualize, and report; Apache Pinot is the store of record that holds the raw tables and full history behind those views. The two overlap wherever the same events, users, and metrics matter to both, and when the bridge between them is a nightly export or a hand-built extract, dashboards lag the warehouse and analysts spend the morning arguing over whose number is right.

Common use cases

  • 01 Feed report metrics into a data model that blends channel performance with conversion and cost data.
  • 02 Pull ranked and trended Reports (metrics by dimension) into Postgres or a warehouse so web and marketing analytics join with CRM, ad-spend, and revenue data in SQL.
  • 03 Push reference and dimension data into Pinot via batch segment loads to enrich event queries.
  • 04 Sync Pinot aggregates into a warehouse to join low-latency metrics with modeled historical data.

Common sync patterns

Where Adobeanalytics produces segments or scores: results back to the warehouse

Cohorts, segments, and computed metrics defined in Adobeanalytics write to Apache Pinot as tables the rest of the stack can query and join.

Shared user and account keys

Users and accounts tracked in Adobeanalytics line up with the customer or user rows in Apache Pinot on a stable key, so both sides count the same population.

Corrections propagate instead of reloading

When a record is fixed or backfilled on one side, the change reaches the other without a full reload, keeping history consistent across both.

What you can sync between Adobeanalytics and Apache Pinot

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Adobeanalytics objects Apache Pinot objects How this pairing syncs
Segments Saved segment definitions used to filter reports, read via GET /segments; cataloged and reused so downstream systems target the same audiences. Segments Immutable data files that batch ingestion uploads and the cluster serves. Same entity on both sides — records pair one-to-one and field-level changes reconcile in the writable direction.
Users Users in the Analytics company, read via GET /users and /users/me; loaded for access, entitlement, and identity reconciliation reporting. Tenants Logical groupings that isolate workloads on shared clusters. Users is specific to Adobeanalytics and Tenants to Apache Pinot — each maps to any object or custom field on the other side.
Usage and Access Logs Admin audit and usage logs of report and tool activity, read via the usage/audit-log endpoints; loaded for security, governance, and adoption reporting. Tables The queryable unit, defined as offline, real-time, or hybrid; the main read target. Usage and Access Logs is specific to Adobeanalytics and Tables to Apache Pinot — each maps to any object or custom field on the other side.
Reports Core reporting endpoint (POST /reports on analytics.adobe.io); returns ranked or trended report data for chosen metrics broken down by dimensions over a date range, with optional segment filters. The main dataset Stacksync reads out. Schemas Column definitions (dimensions, metrics, time columns) mapped during integration setup. Reports is specific to Adobeanalytics and Schemas to Apache Pinot — each maps to any object or custom field on the other side.
Dimensions Available report dimensions (eVars, props, and standard dimensions) per report suite, read via GET /dimensions; pulled as reporting metadata to build report requests and mirror the model. Real-time Tables Tables fed continuously from streams like Kafka, including upsert-enabled tables. Dimensions is specific to Adobeanalytics and Real-time Tables to Apache Pinot — each maps to any object or custom field on the other side.
Metrics Standard metrics available for a report suite, read via GET /metrics; read as metadata to construct report requests and document available measures. Offline Tables Batch-loaded tables merged with real-time data at query time. Metrics is specific to Adobeanalytics and Offline Tables to Apache Pinot — each maps to any object or custom field on the other side.

How changes propagate between Adobeanalytics and Apache Pinot

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Adobeanalytics Apache Pinot Interval-based propagation

DetectionStacksync polls Adobeanalytics for changes on an incremental schedule, reading only records changed since the previous pass. Pull-based over a date range: reports are requested for a from/to window and re-queried on a schedule.

DeliveryEach detected change is applied to Apache Pinot as a row-level write, with types converted between the two schemas.

Apache Pinot Adobeanalytics Interval-based propagation

DetectionStacksync polls Apache Pinot for changes on an incremental schedule, reading only records changed since the previous pass. Data enters Pinot via streaming ingestion or segment upload, not row-level writes.

DeliveryAdobeanalytics does not accept inbound record writes, so this direction carries requests rather than records: Adobeanalytics's output flows back as field updates on the originating Apache Pinot records.

Rate-limit considerations

  • Adobeanalytics: The Analytics 2.0 API enforces 12 requests per 6 seconds (about 120 per minute) per user; exceeding it returns HTTP 429 with error_code 429050. A separate per-report-suite reporting-engine throttle can slow large requests without returning an error.
  • Apache Pinot: No fixed API quotas; query throughput depends on broker and server sizing.
What ships with Adobeanalytics ⇄ Apache Pinot

Connect Adobeanalytics and Apache Pinot for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Adobeanalytics–Apache Pinot connection.

Real-time

Real-time sync

Changes in Adobeanalytics or Apache Pinot instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Adobeanalytics or Apache Pinot data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Adobeanalytics or Apache Pinot record.

Observability

Monitoring

Track your Adobeanalytics ⇄ Apache Pinot sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Adobeanalytics and Apache Pinot.

How the Adobeanalytics and Apache Pinot connectors work

Adobeanalytics

Integration surface
Analytics 2.0 REST API on analytics.adobe.io for reporting and components; Data Feeds and Data Warehouse for raw hit-level export; Data Insertion and Bulk Data Insertion (CSV) APIs for inbound server-side collection.
Authentication
OAuth Server-to-Server via the Adobe Developer Console (JWT service-account auth was deprecated January 1, 2025). The company's global company ID is sent in the x-proxy-global-company-id header, and the integration needs at least the Report Suites, Metrics, and Dimensions permission groups.
Change detection
Pull-based over a date range: reports are requested for a from/to window and re-queried on a schedule. No change-data-capture feed or report-data webhooks; Adobe recommends not polling for new data faster than every 30 minutes and caching results.
Capabilities
read
Rate limits
The Analytics 2.0 API enforces 12 requests per 6 seconds (about 120 per minute) per user; exceeding it returns HTTP 429 with error_code 429050. A separate per-report-suite reporting-engine throttle can slow large requests without returning an error.

Apache Pinot

Integration surface
REST API (SQL queries via the broker; administration via the controller); JDBC client available
Authentication
Deployment-dependent: HTTP basic authentication or token-based auth where enabled
Change detection
Not applicable for reads out (polling by time column); data enters Pinot via streaming ingestion or segment upload, not row-level writes
Capabilities
read · write
Rate limits
No fixed API quotas; query throughput depends on broker and server sizing
How it works

How to connect Adobeanalytics to Apache Pinot — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Adobeanalytics and Apache Pinot with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Adobeanalytics connected
    Apache Pinot connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Adobeanalytics and Apache Pinot objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Adobeanalytics ⇄ Apache Pinot
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Adobeanalytics Apache Pinot
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Adobeanalytics and Apache Pinot integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

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ISO 27001
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→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

Related integrations

Every pair below is a real-time, two-way sync. Search all 368 integrations available for Adobeanalytics and Apache Pinot.

Popular · 8 of 368
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